Person re-IDentification (re-ID) under various occlusions has been a long-standing
challenge as person images with different types of occlusions often suffer from misalignment …

Person re-identification is a challenging research issue in computer vision and has a broad
application prospect in intelligent security. In recent years, with the emergence of large-scale …

The huge variance of human pose and the misalign-ment of detected human images
significantly increase the difficulty of pedestrian image matching in person Re-Identification …

Person re-identification (Re-ID) has undergone a rapid development with the blooming of
deep neural network. Most methods are very easily affected by target misalignment and …

Partial person re-identification (ReID) is a challenging task because only partial information
of person images is available for matching target persons. Few studies, especially on deep …

Various investigations have shown that driver fatigue is the main cause of traffic accidents.
Research on the use of computer vision techniques to detect signs of fatigue from facial …

Unsupervised domain adaptation (UDA) aims to mitigate the domain shift that occurs when
transferring knowledge from a labeled source domain to an unlabeled target domain. While …

Nowadays, with the rapid development of consumer Unmanned Aerial Vehicles (UAVs),
visual surveillance by utilizing the UAV platform has been very attractive. Most of the …

Person retrieval largely relies on the appearance features of pedestrians. This task is rather
more difficult in surveillance videos due to the limitations of extracting robust appearance …

Vehicle Re-Identification (Re-ID) is challenging because vehicles of the same model
commonly show similar appearance. We tackle this challenge by proposing a Global …